Figuring out the “protein folding problem”, that is predicting protein structure from the amino acid sequence, has stood as a grand challenge in biology for the past 50 years. The recent major breakthrough due the advent of artificial intelligence programs such as AlphaFold, seems to have found a solution to this grand challenge, and has demonstrated the impact that AI can have on scientific discovery and its potential to dramatically accelerate progress in fundamental fields.
At the same time, predictions should not be perceived as a way to substitute experimental work. Important challenges are still ahead of us: intrinsically disordered or multidomain proteins, and large complexes. The new tools should be used not to stop structural biology but to push its frontiers. It is then very important to bridge the gap between experimentalists and computational scientists, provide mutual feedback and constitute a forum to discuss on how AI predictions can be integrated in the normal practice of structure determination. To this aim, an EMBO Workshop will be held in Palermo (Italy) on 5th-8th September 2022 (https://meetings.embo.org/event/22-structure-determination). The Workshop program comprises a series of invited talks from experts in the field, as well as a series of oral and poster presentations from selected participants, and will be a great opportunity for structural and computational biologists to meet and discuss the latest developments in the intersection of experimental and computational structure prediction research, as well as help in defining the future direction of inquiries in this area going forward.
The present Research Topic is aimed to gather the proceedings of the EMBO Workshop, as well as to extend the Workshop topics to a wider scientific community and shed light on the future challenges of Structural Biology and integration of AI approaches in its routine.
The Research Topic welcomes articles on, but not limited to, the following topics:
• Experimental and AI approaches in protein structure determination with particular emphasis on intrinsically disordered or multidomain proteins, and large complexes.
• AI approaches in structure determination of proteins with low homology sequence
• Prediction of biomolecules function, including biomolecular interactions (docking)
Figuring out the “protein folding problem”, that is predicting protein structure from the amino acid sequence, has stood as a grand challenge in biology for the past 50 years. The recent major breakthrough due the advent of artificial intelligence programs such as AlphaFold, seems to have found a solution to this grand challenge, and has demonstrated the impact that AI can have on scientific discovery and its potential to dramatically accelerate progress in fundamental fields.
At the same time, predictions should not be perceived as a way to substitute experimental work. Important challenges are still ahead of us: intrinsically disordered or multidomain proteins, and large complexes. The new tools should be used not to stop structural biology but to push its frontiers. It is then very important to bridge the gap between experimentalists and computational scientists, provide mutual feedback and constitute a forum to discuss on how AI predictions can be integrated in the normal practice of structure determination. To this aim, an EMBO Workshop will be held in Palermo (Italy) on 5th-8th September 2022 (https://meetings.embo.org/event/22-structure-determination). The Workshop program comprises a series of invited talks from experts in the field, as well as a series of oral and poster presentations from selected participants, and will be a great opportunity for structural and computational biologists to meet and discuss the latest developments in the intersection of experimental and computational structure prediction research, as well as help in defining the future direction of inquiries in this area going forward.
The present Research Topic is aimed to gather the proceedings of the EMBO Workshop, as well as to extend the Workshop topics to a wider scientific community and shed light on the future challenges of Structural Biology and integration of AI approaches in its routine.
The Research Topic welcomes articles on, but not limited to, the following topics:
• Experimental and AI approaches in protein structure determination with particular emphasis on intrinsically disordered or multidomain proteins, and large complexes.
• AI approaches in structure determination of proteins with low homology sequence
• Prediction of biomolecules function, including biomolecular interactions (docking)
